RESUMO
Cardiac disease and clinical intervention may both lead to an increased risk for thrombosis events due to a modified blood flow in the heart, and thereby a change in the mechanical stimuli of blood cells passing through the chambers of the heart. Specifically, the degree of platelet activation is influenced by the level and type of mechanical stresses in the blood flow. In this article we analyze the blood flow in the left ventricle of the heart through a computational model constructed from patient-specific data. The blood flow in the ventricle is modelled by the Navier-Stokes equations, and the flow through the mitral valve by a parameterized model which represents the projected opening of the valve. A finite element method is used to solve the equations, from which a simulation of the velocity and pressure of the blood flow is constructed. The intraventricular blood flow is complex, in particular in diastole when the inflow jet from the atrium breaks down into turbulent flow on a range of scales. A triple decomposition of the velocity gradient tensor is then used to distinguish between rigid body rotational flow, irrotational straining flow, and shear flow. The triple decomposition enables the separation of three fundamentally different flow structures, that each generates a distinct type of mechanical stimulus on the blood cells in the flow. We compare the results in a simulation where a mitral valve clip intervention is modelled, which leads to a significant modification of the intraventricular flow. Further, we perform a sensitivity study of the results with respect to the positioning of the clip. It was found that the shear in the simulation cases treated with clips increased more compared to the untreated case than the rotation and strain did. A decrease in valve opening area of 64% in one of the cases led to a 90% increase in rotation and strain, but a 150% increase in shear. The computational analysis opens up for improvements in models of shear-induced platelet activation, by offering an algorithm to distinguish shear from other modalities in intraventricular blood flow.
RESUMO
Zebrafish is emerging as a complement to mammals in behavioral studies; however, there is a lack of comparative studies with rodents and humans to establish the zebrafish as a predictive translational model. Here we present a detailed phenotype evaluation of zebrafish larvae, measuring 300-3000 variables and analyzing them using multivariate analysis to identify the most important ones for further evaluations. The dopamine agonist apomorphine has previously been shown to have a complex U-shaped dose-response relationship in the variable distance traveled. In this study, we focused on breaking down distance traveled into more detailed behavioral phenotypes for both zebrafish and rats and identified in the multivariate analysis low and high dose phenotypes with characteristic behavioral features. Further analysis of single parameters also identified an increased activity at the lowest concentration indicative of a U-shaped dose-response. Apomorphine increased the distance of each swim movement (bout) at both high and low doses, but the underlying behavior of this increase is different; at high dose, both bout duration and frequency increased whereas bout max speed was higher at low dose. Larvae also displayed differences in place preference. The low dose phenotype spent more time in the center, indicative of an anxiolytic effect, while the high-dose phenotype had a wall preference. These dose-dependent effects corroborated findings in a parallel rat study and previous observations in humans. The translational value of pharmacological zebrafish studies was further evaluated by comparing the amino acid sequence of the dopamine receptors (D1-D4), between zebrafish, rats and humans. Humans and zebrafish share 100% of the amino acids in the binding site for D1 and D3 whereas D2 and D4 receptors share 85-95%. Molecular modeling of dopamine D2 and D4 receptors indicated that nonconserved amino acids have limited influence on important ligand-receptor interactions.
